The following notebook analyzes gender in STEM publications. The content was developed by Heidi Blackburn and Jason Heppler, University of Nebraska at Omaha. Last updated **April 19, 2019*.
We want to look at two networks:
Graph of authors and publications bimodal network, colored by author and publication.
Graph of authors and their co-authors, colored by gender. (NB: This isn’t working yet.)
NB: The trick here is that there are ties in the dataset, and my code doesn’t account for those ties (it was pretty tricky to get this working). If necessary, I might be able to modify this to try and show all cases where there are ties. Sort by publisher to see the top publishers and their corresponding top three journal titles.
Total percentage increase between 2007 and 2018 across proceedings and journals.
perc_increase_low <- data %>% filter(date == 2007) %>% count()
perc_increase_high <- data %>% filter(date == 2018) %>% count()
paste0(round(perc_increase_high/ perc_increase_low * 100, 2), "%")
## [1] "2420%"